U.S. patent application number 13/842671 was filed with the patent office on 2013-08-22 for system and method of optimal time for product launch and withdraw in e-commerce.
This patent application is currently assigned to ALIBABA GROUP HOLDING LIMITED. The applicant listed for this patent is ALIBABA GROUP HOLDING LIMITED. Invention is credited to Zengguang Liu, Kaili Lv, Jie Su, Zheng Zhang.
Application Number | 20130218702 13/842671 |
Document ID | / |
Family ID | 43732792 |
Filed Date | 2013-08-22 |
United States Patent
Application |
20130218702 |
Kind Code |
A1 |
Lv; Kaili ; et al. |
August 22, 2013 |
SYSTEM AND METHOD OF OPTIMAL TIME FOR PRODUCT LAUNCH AND WITHDRAW
IN E-COMMERCE
Abstract
The present disclosure introduces a technique for achieving the
optimal time to launch or withdraw products on a webpage. In one
aspect, a method includes: storing information to be collected from
a webpage for one or more items corresponding to a first product;
collecting data related to the one or more items in each time
section of a plurality of time sections; calculating a respective
value score for each time section of the plurality of time sections
based on a respective number of occurrences of the one or more
items in each time section; determining the optimal time to launch
or withdraw the first product based on value scores of the first
product for the plurality of time sections; and rendering launch or
withdrawal of the first product on the webpage in the optimal time.
Implementation of the technique will conveniently allow a
merchant's product website to automatically complete a product
launch or withdrawal in the optimal time.
Inventors: |
Lv; Kaili; (Hangzhou,
CN) ; Zhang; Zheng; (Hangzhou, CN) ; Su;
Jie; (Hangzhou, CN) ; Liu; Zengguang;
(Hangzhou, CN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
ALIBABA GROUP HOLDING LIMITED; |
|
|
US |
|
|
Assignee: |
ALIBABA GROUP HOLDING
LIMITED
Grand Cayman
KY
|
Family ID: |
43732792 |
Appl. No.: |
13/842671 |
Filed: |
March 15, 2013 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
12993139 |
Nov 17, 2010 |
8429087 |
|
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13842671 |
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Current U.S.
Class: |
705/26.1 |
Current CPC
Class: |
G06Q 30/02 20130101;
G06Q 10/04 20130101; G06Q 30/0601 20130101; G06Q 30/0641
20130101 |
Class at
Publication: |
705/26.1 |
International
Class: |
G06Q 30/06 20120101
G06Q030/06 |
Foreign Application Data
Date |
Code |
Application Number |
Sep 11, 2009 |
CN |
200910176254.8 |
Claims
1. An electronic commerce (e-commerce) system, comprising: a
webpage information collection processing unit that collects one or
more items corresponding to a first product on a webpage, the one
or more items including information of one or more users who have
visited the webpage in each time section; a time section value
score calculation unit that calculates a respective value score for
each of a plurality of time sections by using an algorithm based on
a respective number of occurrences of one or more items in each
time section; and a product launch/withdrawal optimal time
determination unit that determines an optimal time to launch or
withdraw the first product from the plurality of time sections
based on the respective value score for each of the plurality of
time sections.
2. The e-commerce system as recited in claim 1, further comprising
a product launch/withdrawal processing unit that renders a product
launch or withdrawal of the first product in the optimal time.
3. The e-commerce system as recited in claim 1, further comprising
a time section determination unit that determines the plurality of
time sections based on a first time limit when a number of users
who has visited the webpage during the first time limit reaches a
first predefined value, a second time limit when a number of orders
placed on the first product during the second time limit reaches a
second predefined value, a third time limit when a total amount of
one or more orders placed on the first product during the third
time limit reaches a third predefined value, or a predefined time
limit.
4. The e-commerce system as recited in claim 1, further comprising
a product launch/withdrawal reference processing unit that
identifies a second product that is similar to the first product,
determines a launch or withdrawal optimal time corresponding to the
second product based on the optimal time for the first product, and
renders the product launch or withdrawal of the first product in
the optimal time corresponding to the second product.
5. The e-commerce system as recited in claim 1, further comprising
a webpage information collection interactive interface that accepts
data from a user to collect information of the one or more items
corresponding to the first product.
6. The e-commerce system as recited in claim 1, further comprising
a database, wherein the database further comprises a product
optimal time data storage unit that stores the optimal time for
launch or withdrawal of the first product as determined by the
product launch/withdrawal optimal time determination unit.
7. The e-commerce system as recited in claim 1, wherein the one or
more items further include a time of a user's visit to the webpage
and a time of an order placed by the user.
8. The e-commerce system as recited in claim 1, wherein the time
section value score calculation unit calculates the respective
value score for each of the plurality of time sections by using a
formula of sum(t)=q.sub.1*m.sub.1+q.sub.2*m.sub.2 +. . .
+q.sub.n,*m.sub.n, wherein q.sub.1, q.sub.2 . . . q.sub.n each
represents a respective weight of the respective item in the one or
more items in a respective time section, m.sub.1, m.sub.2 . . .
m.sub.n, each represents the respective number of occurrences of
the respective item in the respective time section, and sum (t)
represents the respective value score of the respective time
section.
9. The e-commerce system as recited in claim 8, wherein when the
formula is in a form of sum(t)=q.sub.1*m.sub.1+q.sub.2*m.sub.2,
m.sub.1 is a number of users who has visited the webpage in a
respective time section t, m.sub.2 is a number of orders placed in
the respective time section t, q.sub.1 is a weight for m.sub.1, and
q.sub.2 is a weight for m.sub.2.
10. A method comprising: collecting one or more items corresponding
to a first product on a webpage; calculating a respective value
score for each of a plurality of time sections based on a
respective value of each of the one or more items for each of the
plurality of time sections; and determining an optimal time to
launch or withdraw the first product from the plurality of time
sections based on the respective value score for each of the
plurality of time sections.
11. The method as recited in claim 10, further comprising rendering
a launch or withdrawal of the first product in the optimal
time,.
12. The method as recited in claim 10, further comprising:
identifying a second product that is similar to the first product;
determining an optimal time corresponding to the second product
based on the optimal time corresponding to the first product; and
rendering a launch or withdrawal of the second product in the
optimal time corresponding to the second product.
13. The method as recited in claim 10, wherein the determining an
optimal time to launch or withdraw the first product comprises
determining a time section with a highest value score as the
optimal time.
14. The method as recited in claim 10, wherein the one or more
items include a time of a user's visit to the webpage, information
of the user, and a time of an order placed by the user.
15. The method as recited in claim 10, wherein the calculating the
respective value score for each of the plurality of time sections
comprises: calculating the respective value score for each of the
plurality of time sections by using a formula of
sum(t)=q.sub.1*m.sub.1+q.sub.2*m.sub.2 +. . . +q.sub.n*m.sub.n,
wherein q.sub.1, q.sub.2 . . . q.sub.n each represents the
respective weight of the respective item in the one or more items
in a respective time section, m.sub.1, m.sub.2 . . . m.sub.n each
represents a respective number of occurrences of the respective
item in the respective time section, and sum (t) represents the
respective value score of the respective time section.
16. The method as recited in claim 13, wherein the formula is in a
form of sum(t)=q.sub.1*m.sub.1+q.sub.2*m.sub.2, m.sub.1 is a number
of users who has visited the webpage in a respective time section
t, m.sub.2 is a number of orders placed in the respective time
section t, q.sub.1 is a weight for m.sub.1, and q.sub.2 is a weight
for m.sub.2.
17. The method as recited in claim 10, further comprising
determining the plurality of time sections based on a first time
limit when a number of users who has visited the webpage during the
first time limit reaches a first predefined value, a second time
limit when a number of orders placed on the first product during
the second time limit reaches a second predefined value, a third
time limit when a total amount of one or more orders placed on the
first product during the third time limit reaches a third
predefined value, or a predefined time limit.
18. The method as recited in claim 10, further comprising
determining the plurality of time sections, wherein the determining
comprises: determining if a number of users who has visited the
webpage has reached or exceeded a predefined value in a predefined
time limit; increasing the predefined time limit to a new time
limit when the number of users who visited the webpage has not
reached or exceeded the predefined value in the predefined time
limit until the number of users who visited the webpage has reached
or exceeded the predefined value in the time limit; and setting the
new time limit as a duration of a time section.
19. A method comprising: determining a plurality of time sections
based on a time limit when a number of users who has visited the
webpage during the time limit reaches a predefined value;
calculating a respective value score for each of the plurality of
time sections; and determining an optimal time to launch or
withdraw the first product from the plurality of time sections
based on the respective value score for each of the plurality of
time sections.
20. The method as recited in claim 19, further comprising:
identifying a second product that is similar to the first product;
determining an optimal time to launch or withdraw the second
product from the plurality of time sections based on the optimal
time to launch or withdraw the first product; and rendering a
launch or withdrawal of the second product in the optimal time to
launch or withdraw the second product.
Description
CROSS REFERENCE TO RELATED PATENT APPLICATIONS
[0001] This application is a continuation of and claims priority to
U.S. patent application Ser. No. 12/993,139, filed on Nov. 17,
2010. U.S. patent application Ser. No. 12/993,139 is a national
stage application of an international patent application
PCT/US2010/048281, filed Sep. 9, 2010, which claims priority from
Chinese Patent Application No. 200910176254.8, filed Sep. 11, 2009,
and entitled "SYSTEM AND METHOD OF OPTIMAL TIME FOR PRODUCT LAUNCH
AND DELAUNCH IN E-COMMERCE", which applications are hereby
incorporated in their entirety by reference.
TECHNICAL FIELD
[0002] The present disclosure relates to the field of Internet
technology and, more specifically, to an electronic commerce, or
e-commerce, system and method for achieving the optimal time to
launch or withdraw products.
BACKGROUND OF THE PRESENT DISCLOSURE
[0003] With the advancement of modern information technology,
web-based transactions are finding favor and getting more attention
from people. Web-based transactions are not subject to territorial
limitations (especially remote suburbs and counties) and are not
limited by office hours. As long as the requirements for secure
online transactions are in place, anyone can easily and
conveniently order online from home or from the office.
[0004] FIG. 1 is a schematic diagram of the fundamental structure
of a commonly seen e-commerce system, which consists of client
terminal 11, merchant terminal 12, and e-commerce platform 13.
Client terminal 11, merchant terminal 12 and electronic commerce
(hereinafter "e-commerce") platform 13 are connected to each other
through the Internet. Merchant terminal 12 creates a corresponding
merchant name in the e-commerce platform 13, and displays the
merchant's products through the e-commerce platform 13. Usually,
all the products of a given merchant (also called the merchant's
virtual store products) are set-up in linked web pages. The virtual
store information of different merchants are set up in each
e-commerce platform 13, even the information of other e-commerce
platforms are set up, and through the e-commerce platform 13,
product information of other merchants are displayed. Client
terminal 11 logs into e-commerce platform 13 through the Internet,
and selects the desired products to buy from the merchant virtual
stores. The settlement of goods payments between client terminal 11
and merchant terminal 12 can be done through third-party payment
platforms, express delivery companies, or banks or other financial
institutions with financial systems for settling goods payments.
What needs to be emphasized is that there are no strict boundaries
between merchant terminal 12 and client terminal 11, because many
merchants are also buyers. Therefore, the merchant terminal 12 and
client terminal 11 mentioned in this present disclosure are
separated for the purpose of explaining the application's proposed
techniques, and not to restrict all product providers as merchant
terminal 12 or all buyers as client terminal 11.
[0005] The e-commerce platform 13 mainly includes server 131 and
database 132. Database 132 is used mainly to store merchant
information, including the merchant name, product information,
client information and product transaction information. Server 131
mainly consists of an interface display processing unit, an
interactive processing unit and a transaction processing unit. The
interface display processing unit is used to display product
information. The interactive processing unit is used to process the
interaction between the merchant and the client. The transaction
processing unit is used to process the transaction.
[0006] The merchants that sign contracts with e-commerce platform
13 are big companies. Each merchant supplies numerous products, and
there is a level of difficulty for the interface display processing
unit to display the merchants' products. A commonly used method of
the interface display processing unit to control product display is
discussed below.
[0007] First, each merchant is provided with the webpage address
that displays their product information. Next, rules for displaying
the products are established. The display rules can stipulate that
the products of a merchant should not be in the `launch` state from
start to finish. Product launch refers to the product information
appearing in the e-commerce platform 13, which provides the
information to the merchant's webpage and all its subpage systems,
where said subpage systems refers to the merchant's webpage
subpages, the subpages' succeeding subpages, etc.
[0008] The interface display processing unit will check if the
merchant's webpage and its subpages contain products that have
reached a predefined maximum launch period (e.g. 7 days). If yes,
the product will undergo a withdrawal process. Withdrawal process
means that a product's webpage will be disconnected, so that
clients will not be able to visit the webpage. As for product
launching, the merchant, based on its own experience, should launch
a product at the time when there are many visitors and
transactions.
[0009] Besides product launching and withdrawal, the interface
display processing unit controls the merchant's product list. The
product information that is nearest the withdrawal time is to be
displayed at the top of the list. The interface display processing
unit allows the corresponding webpages of the products that are
displayed at the top of the product list to be easily visited by
the clients.
[0010] The current methods of launching or withdrawing products
have the following drawbacks:
[0011] First, there are no unified rules on product launching. The
e-commerce platform has no way to control the launching of
products, and it can only use its self-defined rules (e.g., at the
start, merchants can launch no more than 10 products) to singularly
control whether a product can be launched or not. However, it
cannot provide controls targeted at specific products (or product
groups). For example, reading glasses for old people are typically
better launched in the morning than in the evening, and fashionable
items for young people are typically better launched in the evening
or afternoon than in the morning. The merchant only decides when to
launch products based on the merchant's own experience. This method
of launching products is difficult for the merchants, especially if
launching numerous products. A merchant can easily miss out on an
opportunity for a sale due to inaccurate product launch times.
[0012] Next, the interface display processing unit checks the
merchant's webpage and its subpages for products that have reached
the predefined maximum launch period (e.g., 7 days). These products
will undergo the withdrawal process. This method of controlling the
withdrawal process also causes technical inconsistencies. For
example, a certain product has been sold out, but the merchant
forgets to withdraw the product. If the above-mentioned way of
processing is allowed to continue, the sold-out product will
utilize a huge amount of resources, resulting in wastage.
[0013] Lastly, the product information that is nearest the
withdrawal time is displayed at the top of the product list. When
there are many products being launched, the interface display
processing unit needs to utilize a huge amount of time and
resources to arrange and display the items in the product list,
thus wasting resources and causing a delay in providing information
to clients.
SUMMARY OF THE DISCLOSURE
[0014] The present disclosure introduces an e-commerce system for
achieving the optimal time to launch or withdraw products, and to
solve the problem with the current technology that uses up a large
amount of the system's resources for launching or withdrawing
products and is unable to realistically provide a merchant with
product launching or withdrawal time.
[0015] Another purpose of the present disclosure is to provide a
method for achieving the optimal time to launch or withdraw
products, and to solve the problem with the current technology that
uses up a large amount of the system's resources for launching or
withdrawing products and is unable to realistically provide a
merchant with product launching or withdrawal time.
[0016] In one aspect, an electronic commerce (e-commerce) system
comprises a database and a server communicatively coupled to the
database.
[0017] The database may comprise a webpage collection and item
storage unit that stores information to be collected from a webpage
for one or more items corresponding to a first product.
[0018] The server may comprise: a webpage information collection
processing unit, a time section value score calculation unit, a
product launch/withdrawal optimal time determination unit, and a
product launch/withdrawal processing unit. The webpage information
collection processing unit may gather item related data to be
collected by the webpage. The time section value score calculation
unit may calculate a respective value score for each of a plurality
of time sections. The product launch/withdrawal optimal time
determination unit may determine a optimal time to launch or
withdraw the first product based on value scores of the first
product for the plurality of time sections. The product
launch/withdrawal processing unit may render product launch or
withdrawal of the first product in the optimal time.
[0019] In one embodiment, the server may further comprise a time
section determination unit. The time section determination unit may
determine if a number of clients who visited the webpage has
reached or exceeded a predefined value in a predefined time limit.
The time section determination unit may increase the time limit to
a new time limit when the number of clients who visited the webpage
has not reached or exceeded the predefined value in the predefined
time limit until the number of clients who visited the webpage has
reached or exceeded the predefined value in the time limit. The
time section determination unit may set the new time limit as a
duration of the respective time section.
[0020] In one embodiment, the server may further comprise a product
launch/withdrawal reference processing unit. The product
launch/withdrawal reference processing unit may identify a second
product that is similar to the first product, determine a launch or
withdrawal optimal time corresponding to the second product, and
render the product launch or withdrawal of the first product in the
optimal time corresponding to the second product.
[0021] In one embodiment, the server may further comprise a webpage
information collection interactive interface. The webpage
information collection interactive interface may accept data from a
user to collect information of the one or more items corresponding
to the first product.
[0022] In one embodiment, the database may further comprise a
product optimal time data storage unit. The product optimal time
data storage unit may store a respective optimal time for launch or
withdrawal of the first product as determined by the product
launch/withdrawal optimal time determination unit.
[0023] In one embodiment, the time section value score calculation
unit may calculate a respective value score for each of the
plurality of time sections based on a respective number of
occurrences of the one or more items in each time section.
[0024] In one embodiment, the information to be collected by the
webpage may include: a time of a user's visit to the webpage,
information of the user who visited the webpage, and a time of an
order placed by the user.
[0025] In one embodiment, the time section value score calculation
unit may calculate a respective value score for each of the
plurality of time sections by using a formula of
sum(t)=q.sub.1*m.sub.1+q.sub.2*m.sub.2+ . . . +q.sub.n*m.sub.n,
wherein q.sub.1, q.sub.2 . . . q.sub.n each represents a respective
proportion of respective item data that needs to be gathered by the
webpage, m.sub.1, m.sub.2 . . . m.sub.n each represents a
respective number of occurrences of a respective item in the time
section, and sum (t) represents the value score of the time
section. When the formula is in the form of
sum(t)=q.sub.1*m.sub.1+q.sub.2*m.sub.2, m.sub.1 is a number of
users who have visited the webpage in a time section t, m.sub.2 is
a number of orders placed in the time section t, q.sub.1 is a
weight for m.sub.1, and q.sub.2 is a weight for m.sub.2.
[0026] In another aspect, a method for achieving product launch or
withdraw on a webpage at an optimal time is provided. The method
may comprise: storing information to be collected from a webpage
for one or more items corresponding to a first product; collecting
data related to the one or more items in each time section of a
plurality of time sections; calculating a respective value score
for each time section of the plurality of time sections based on a
respective number of occurrences of the one or more items in each
time section; determining the optimal time to launch or withdraw
the first product based on value scores of the first product for
the plurality of time sections; and rendering launch or withdrawal
of the first product on the webpage in the optimal time.
[0027] In one embodiment, the method may further comprise:
identifying a second product that is similar to the first product;
determining a corresponding optimal time for product launch of the
second product; and rendering product launch for the first product
on the webpage in the corresponding optimal time for product launch
of the second product.
[0028] In one embodiment, the method may further comprise:
providing an interface for a user to enter information to be
collected from the webpage for one or more items corresponding to
one or more products; storing the information for the one or more
items corresponding to one or more products as entered by the user,
the information including criteria for calculating value scores and
respective weights of each of the one or more items; and
calculating the value scores for the plurality of time sections
based on the information entered by the user.
[0029] In one embodiment, calculating a respective value score for
each time section of the plurality of time sections may comprise:
calculating a respective value score for each of the plurality of
time sections by using a formula of
sum(t)=q.sub.1*m.sub.1+q.sub.2*m.sub.2+ . . . +q.sub.n*m.sub.n,
wherein q.sub.1, q.sub.2 . . . q.sub.n each represents a respective
proportion of respective item data that needs to be gathered by the
webpage, m.sub.1, m.sub.2 . . . m.sub.n each represents a
respective number of occurrences of a respective item in the time
section, and sum (t) represents the value score of the time
section.
[0030] In one embodiment, storing information to be collected from
the webpage for the one or more items corresponding to the first
product may comprise: determining a lowest time limit and a highest
time limit; setting the lowest time limit as a default time limit;
assessing whether a number of client visit to the webpage has
exceeded a predefined value in the default time limit; increasing
the default time limit when the number of client visit to the
webpage has not exceeded the predefined value in the default time
limit; and setting the default time limit as a duration of the
respective time section when the number of client visit to the
webpage has exceeded the predefined value in the default time
limit.
[0031] In one embodiment, determining the optimal time may comprise
determining a time section with a highest value score to be the
optimal time.
[0032] Compared with the current technology, the technique provided
in the present disclosure has a number of advantages. First, the
present disclosure controls the merchant's products, and
automatically completes the product launching or withdrawal, so
there is no need for the merchant to control this process, thus
avoiding confusion on the merchant's part. The e-commerce platform
does not need additional resources to check for mix-ups in the
product launching or withdrawal process. Next, the proposed
technique focuses on the merchant and provides self-adaptive
launching or withdrawal time for the merchant's unique products. It
is convenient for the merchant to implement, the calculation method
is simple, and the product launching or withdrawal will be
automatically completed at the optimal times. Lastly, the present
disclosure will trigger the withdrawal process for a product that
has been sold-out, so that the product will not use up additional
resources. This will result in enhanced resource utilization.
BRIEF DESCRIPTION OF THE DRAWINGS
[0033] FIG. 1 is a diagram of a conventional e-commerce system.
[0034] FIG. 2 is a diagram of an e-commerce system in accordance
with the present disclosure.
[0035] FIG. 3 is a diagram of the fundamental structure of an
e-commerce platform in accordance with the present disclosure.
[0036] FIG. 4 is a flowchart of a method for achieving the optimal
time for product launching or withdrawal in accordance with the
present disclosure.
DETAILED DESCRIPTION
[0037] FIG. 2 illustrates an e-commerce system for achieving the
optimal time to launch or withdraw products in accordance with the
present disclosure. The system comprises the E-Commerce Platform
23, Merchant Terminal 22, and Client Terminal 21. The E-Commerce
Platform 23, Merchant Terminal 22, and Client Terminal 21 are
communicatively coupled to each other through one or more networks,
such as the Internet and wireless communication networks.
[0038] Client Terminal 21 and Merchant Terminal 22 can either be
network terminals or portable terminals such as mobile phones.
Client Terminal 21 and Merchant Terminal 22 can also be nodes in a
local area network (LAN). In principle, Client Terminal 21 and
Merchant Terminal 22 can log into the E-Commerce Platform 23
through the network.
[0039] From a logical point of view, the E-Commerce Platform 23
comprises a Database 31 and a Server 32 communicatively coupled to
Database 31, as shown in FIG. 3. In one embodiment, Database 31 and
Server 32 are both implemented in a single processor-based server.
Alternatively, Database 31 is implemented in one or more
processor-based servers different from Server 32. In one
embodiment, Server 32 is implemented in one or more processor-based
servers.
[0040] Referring to FIG. 3, Database 31 includes components as
described below.
[0041] Webpage Collection and Item Storage Unit 311 stores the
information to be collected from a webpage for one or more items
corresponding to a product. When the system (such as the E-Commerce
Platform 23) provides a merchant with software for achieving the
optimal time for launching or withdrawing products, the system can
initially provide default item information for the product to be
collected. For example, the items the information of which is to be
collected may include the following: frequency of client visits for
each product of the merchant on the webpage, duration of the visit,
the time when the client orders and buys a certain product, etc.
Aside from the item name, the item information of an item may also
include a proportion of the item among all the items the
information of which is to be collected. In one embodiment, the
information to be collected by the webpage includes: includes: a
time of a client's visit to the webpage, information of the client
who visited the webpage, and a time of an order placed by the
client.
[0042] In some embodiments, the Webpage Collection and Item Storage
Unit 311 can store the webpage item information for a product that
is entered by the merchant. Each merchant can also establish the
item information that needs to be collected by each product's
corresponding webpages.
[0043] Product Optimal Time Data Storage Unit 312 stores the
respective optimal time for launching or withdrawing each product.
The Product Optimal Time Data Storage Unit 312 can store not only
the optimal time for launching a certain product of a certain
merchant, but can also save both the optimal time for launching and
the optimal time for withdrawing products. Usually, a product's
withdrawal typically coincides with another product's launch, thus
the embodiment only stores the optimal time for launching a certain
product of a certain merchant, which is approximately the same time
as the withdrawal of another product. In addition, the time limit
for a product's launching and withdrawal can be set. For example, a
product's launch date is set for January 1, 3 PM. The withdrawal
date can be set for January 8, 3 PM, or be withdrawn once it is
sold out even if it has not yet reached the withdrawal due
date.
[0044] In one embodiment, considerations are made from the
perspective of the merchant, by storing the launch optimal time and
withdrawal optimal time of all the products of the merchant. If we
consider that many merchants have many products, and if we storage
the launch optimal time and withdrawal optimal time of all the
products, this will increase the required storage space usage. The
Product Optimal Time Data Storage Unit 312 can be configured to
store only the launch optimal time of the predefined products of
the merchant.
[0045] In one embodiment, the Server 32 includes:
[0046] Webpage Information Collection Interactive Interface 321
accepts data entered by a user, such as a merchant, to collect
information related to one or more items corresponding to the
product. For example, Webpage Information Collection Interactive
Interface 321 provides an interface to a merchant, where the
merchant can enter item information for the merchant's products
listed on the webpage. The item information collected from the
merchant may include name of the item, a proportion of the item
among all the items the information of which is to be collected,
etc. Considering that the item information provided by each
merchant can be varied and different, there may be a level of
difficulty in gathering together all the item information, and
thus, this sample embodiment enumerates only the items that have
been predefined to be collected. In general, this method will be
able to provide collected webpage information that can satisfy
individual requirements.
[0047] Time Section Determination Unit 322 determines if the number
of clients who have visited the webpage has reached or exceeded a
predefined value in a predefined time limit. The Time Section
Determination Unit 322 may increase the time limit if the
predefined value has not been reached or exceeded, until it is
determined that the number of clients who have visited the webpage
has reached or exceeded the predefined value. The corresponding
time limit with increased length may be set as the duration of the
time section. Aside from determining if the number of clients who
have visited the webpage has reached or exceeded the predefined
value, the Time Section Determination Unit 322 can also determine
if the frequency of visits to the webpage has reached or exceeded a
predefined frequency in the predefined time limit. The principle of
operation is the same, so detailed description will not be provided
in the interest of brevity. The time limit may be within one day or
more than one day, but usually is set to be within one day.
[0048] Assuming the predefined time limit is 1 hour and the
requirement is to have at least 3 client visits to the
corresponding product webpage within the time limit of 1 hour, the
Time Section Determination Unit 322 can assess if there are 3
clients who have visited the product webpage in the time limit of 1
hour. If the number of visits is at least 3, then the current time
limit (1 hour) may be set as the duration of the time section. In
other words, the 24 hours of a day can be divided into 24 time
sections, each with 1 hour as the duration. On the other hand, if
fewer than 3 clients have visited the product webpage within the
time limit, then the Time Section Determination Unit 322 may
increase the time limit. For example, the Time Section
Determination Unit 322 may increase the time limit to 1.5 hours,
and then determine again if within the 1.5-hour period there are at
least 3 clients who have visited the product webpage. The Time
Section Determination Unit 322 may repeat this process until it
reaches a new time limit within which there are at least 3 clients
who have visited the product webpage. This new time limit may then
be set as the duration of the time section.
[0049] In one embodiment, the Time Section Determination Unit 322
can use the volume of orders for a product to evaluate the time
limit. For example, when the number of orders for a particular
product has reached a predefined number of orders within a time
limit, such time limit may be set as the duration of the time
section. As another example is, if within a time limit the monetary
amount of orders for a particular product has reached a predefined
amount, then the time limit may be set as the duration of the time
section.
[0050] In one embodiment, the Time Section Determination Unit 322
may be optional. In such case the system may use a default time
section, such as a one-hour time section with 24 time sections in a
day, for example.
[0051] Webpage Information Collection Processing Unit 323 gathers
related item data to be collected by the webpage in each time
section. The Webpage Information Collection Processing Unit 323 is
usually connected to an existing interface display processing unit,
or combined with the interface display processing unit.
[0052] To illustrate using the frequency of visits to a certain
webpage as an example, after the Webpage Information Collection
Processing Unit 323 receives notification that the webpage has been
clicked, it will increment the frequency of client visits to the
webpage by 1. Clients coming from the same IP address may be
considered as one and the same client. After the Webpage
Information Collection Processing Unit 323 receives notification
that the webpage has been clicked, it will compare the client's IP
address with saved IP addresses of clients that have visited the
webpage. If there is no matching IP address, the Webpage
Information Collection Processing Unit 323 will save the client's
IP address, and increment the frequency of client visit to the
webpage by 1. However, visitors to a webpage are not necessarily
buyers, but can also be merchants as well. Clients and merchants
normally will first sign up as members in the E-Commerce Platform
23. When the Webpage Information Collection Processing Unit 323
receives notification that the webpage has been clicked, it will
check the information of the member who clicked the webpage, save
the member's ID, and increment the frequency of client visit to the
webpage by 1. If the client who clicked the webpage has already
clicked the webpage in the current time section, another option is
not to increment the frequency of client visit to the webpage. The
frequency of client visit to a webpage is calculated based on
predefined rules.
[0053] Time Section Value Score Calculation Unit 324 calculates a
respective value score for each time section of a plurality of time
sections. This can be done, for example, by using the formula
sum(t)=q.sub.1*m.sub.1+q.sub.2*m.sub.2 +. . . +q.sub.n*m.sub.n,
where q.sub.1, q.sub.2 . . . q.sub.n each represents a respective
proportion of respective item data that needs to be gathered by the
webpage, m.sub.1, m.sub.2 . . . m.sub.n each represents a
respective number of occurrences of a respective item in the time
section, and sum (t) represents the value score of the time
section.
[0054] For example, in sum(t)=q.sub.1*m.sub.1+q.sub.2*m.sub.2,
m.sub.1 is the number of clients who have visited the homepage in
the time section t, m.sub.2 is the number of times the clients
ordered in the time section t, q.sub.1 is the weight for the user's
visit to the homepage, and q.sub.2 is the weight for the user's
order.
[0055] Product Launch/Withdrawal Optimal time Determination Unit
325 determines the optimal time to launch or withdraw a product,
based on the product's value score for each time section.
[0056] In one embodiment, the launch time is the time section with
the highest value score.
[0057] Product Launch/Withdrawal Processing Unit 326 renders the
launch or withdrawal of a product in the optimal time to consummate
the product launch or withdrawal.
[0058] When the product is to be launched, the Product
Launch/Withdrawal Processing Unit 326 can refer to the optimum
launch time of a previously launched similar (or same type of)
product, and proceed to launch the product in concern during that
optimal time. In one embodiment, the product can be launched in the
time section with the highest value score, or launched before
reaching the time section with the highest value score. After the
product has been launched, the optimal time for launching may be
calculated and stored in the Product Optimal time Data Storage Unit
312. This will serve as reference for future launch of similar (or
same type of) products.
[0059] In one embodiment, the Product Launch/Withdrawal Processing
Unit 326 can also be used to calculate the transaction volume of a
product. For example, once the transaction volume has reached a
predefined total for the product, the product may be withdrawn.
[0060] In one embodiment, the Server 32 also includes a Product
Launch/Withdrawal Reference Processing Unit 327. The Product
Launch/Withdrawal Reference Processing Unit 327 finds a product
that is similar to the product in concern, identifies a launch or
withdrawal optimal time corresponding to the similar product, and
renders the product launch or withdrawal of the product in concern
in the optimal time corresponding to the similar product.
[0061] The above-described units may be logically separate, and may
also be physically separate. Usually, they are logically separate.
These units are usually implemented using software modules in one
or more hardware platform. For example, we can create software for
the optimal time for launch or withdrawal of one or more products,
and then install the software in a merchant's virtual store. When a
product needs to be launched, the software can search for the
optimal time to launch the product, and then automatically launch
the product in the identified optimal time. When a product needs to
be withdrawn, the software can search for the optimal time to
withdraw the product, and then automatically withdraw the product
in the identified optimal time.
[0062] FIG. 4 illustrates a flow diagram for a method, or process,
of achieving the optimal time for launching or withdrawing a
product, as mentioned in this present disclosure. The process
includes a number of actions as described below.
[0063] S110: The process sets and stores information to be
collected from a webpage for one or more items corresponding to a
product.
[0064] The item information may be the default item information
provided by the system, and may also be item information provided
by the merchant. Item information may include: frequency of a
client visit to the product's webpage, client order information,
and so on.
[0065] In one embodiment, the process may provide an interface for
a user to enter information to be collected from the webpage for
one or more items corresponding to one or more products. The
process may store the information for the one or more items
corresponding to one or more products as entered by the user. The
information may include: criteria for calculating value scores and
respective weights of each of the one or more items. The process
may calculate the value scores for the plurality of time sections
based on the information entered by the user.
[0066] S120: In each time section, the process gathers data related
to the item collected by the webpage.
[0067] When the merchant opens the function for achieving the
optimal time for launch or withdrawing products, and after the
system has retrieved the previously saved item information to be
collected by the webpage, the process may trigger operational
instructions on how to collect the data for each item. When the
webpage has been visited and has satisfied the trigger conditions,
the process will follow the operational instructions to finish
collecting the corresponding item related data.
[0068] The item related data may be the item related data for any
time period. For example, if it is desired to collect the item
related data from 8 AM to 9 AM, the process may collect the item
related data at 10 AM. Of course, it is possible to defer to the
system's processing state to decide what time to collect the item
data. For example, the system may be not busy from 1 AM to 5 AM, so
it may be ideal to trigger the operational instructions to collect
the item data at 2 AM, for example.
[0069] S130: The process calculates a respective value score for
each time section. In the formula
sum(t)=q.sub.1*m.sub.1+q.sub.2*m.sub.2 +. . . +q.sub.n*m.sub.n,
each of q.sub.1, q.sub.2 . . . q.sub.n is the respective proportion
of the respective item related data that needs to be collected by
the webpage, each of m.sub.1, m.sub.2, . . . m.sub.n is the
respective number of occurrences of the respective item in the
specific time section, and t in sum(t) is the value score for the
time section.
[0070] The time section can be predefined, such as dividing one day
into 24 time sections, with 1 hour for each time section. A time
section can also be derived using steps described below.
[0071] A1: Determine the lowest and the highest time limits.
[0072] "Time limit" refers to the time limit for gathering item
information. The lowest time limit and the highest time limit refer
to the expected lowest time limit and highest time limit,
respectively. The shorter the time limit, the more item collection
the system needs to carry out and thus more system resources are
used. Therefore, the lowest time limit needs to be predefined. When
the time limit is high enough, the related item information
collected cannot be used as the basis for future launch or
withdrawal. Therefore, the lowest time limit and the highest time
limit need to be predefined.
[0073] A2: Set the lowest time limit as the time limit.
[0074] A3: Assess if the number of client visit to the webpage has
exceeded the predefined value in the time limit. If not, proceed to
A4; otherwise the current time limit will be set as the duration of
the time section;
[0075] A4: Increase the time limit. If the time limit is not higher
than the highest time limit, then go to A3; otherwise exit. The
length of time by which the time limit is to be increased can be
predetermined.
[0076] This method can determine the corresponding time limit based
on each merchant's specific situation.
[0077] The formula for calculating the value score can be provided
by the system. The merchant can also set the item and the
proportion it occupies.
[0078] S140: Based on a product's value score for each time
section, the process determines the optimal time to launch or
withdraw the product.
[0079] In normal situations, the time section with the highest
value score may be considered as the optimal time for launching the
product or similar products. The time section with the lowest value
score may be considered as the optimal time for withdrawing the
product or similar products.
[0080] S150: The process renders the product launch or withdrawal
in the optimal time for product launch or withdrawal on the
webpage.
[0081] When a new product is first launched, there is no product
history value score from which to obtain the optimal time.
Therefore, the process may first identify a product that is similar
to the new product, determine the corresponding optimal time for
product launch of the similar product, then render the product
launch for the new product on the webpage in the corresponding
optimal time for product launch of the similar product.
[0082] After a product has been launched once, and when it is to be
launched again, the system can consider the product's previous
launch time to trigger the product launch. The product's
transaction volume can be determined. Once the product's
transaction volume has reached the predefined total for the product
then the product may be withdrawn.
[0083] The above described process can be implemented in software
or hardware. In one embodiment, the above described process can be
implemented in the form of computer-executable instructions or code
stored on one or more computer-readable storage media that, when
executed by one or more processors of one or more computing
devices, can cause the one or more computing devices to carry out
the process. The one or more computer-readable storage media may
be, for example, compact disc such as CD/ROM, flash memory, EEPROM,
internal or external hard drive, USB drive, or any memory device
that can store data or computer-executable instructions.
[0084] The present disclosure provides only a few sample
embodiments. However, the present disclosure is not limited by
these examples, and any changes proposed by persons in this
technical field will be considered under the protection of the
present disclosure.
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